Combining field-level data and remote sensing to understand impact of management practices on producer yields

Producer field-level data have been used in recent studies to identify suites of management practices that consistently increase yield for a given climate-soil environment. However, the physiological drivers underlying the empirical associations between yield and management practices derived from these studies have remained mostly speculative, particularly in terms of resource capture and conversion into economic yield. We followed an approach consisting of a large producer database, satellite imagery, and crop modeling to assess which key physiological parameters best explain on-farm yield response to producer-chosen management practices across different climate-soil production environments. Survey data on yield and management practices were collected from 5291 soybean fields sown across the US North Central region during 2014-2016. Producer data were grouped into 10 technology extrapolation domains (TEDs) to account for variation in soil, climate, and water regime across producer fields. Simulated phenology and satellite imagery were used to estimate incident (IPAR) and absorbed (APAR) photosynthetically active radiation during the entire crop season and also during the time-span beginning with pod setting and ending with physiological maturity. In each TED, seed yield was increased by early sowing (+13 to +39 kg ha^-1d^-1), which was physiologically driven by increases in the duration of both crop cycle and critical period, and by a higher APAR. In-season application of foliar fungicide and/or insecticide also resulted in significant yield increase (+0.35 Mg ha⁻¹, p < 0.01) that was mediated by improvement in the efficiency in converting capture radiation into seed yield (e_c) and, to a lesser degree, efficiency at capturing incident radiation (e_a) and APAR. Tilled fields had greater yield than no-tilled fields (+0.12 Mg ha^-1, p < 0.01), which was driven by slight improvements in e_c and APAR, and partially attributable to earlier sowing. The proposed approach provides new opportunities to understand underlying mechanisms explaining on-farm yield variation due to management and identify alternatives for increasing yield and crop efficiencies in the use of inputs and resources.